In our previous blog post, we delved into the concept of Cluster API (CAPI) and its potential to simplify Kubernetes cluster management. We explored its principles, benefits, and how it streamlines the lifecycle of Kubernetes clusters.
In this sequel, we'll embark on a hands-on journey to harness the power of Cluster API for real-world Kubernetes cluster management. We'll provide step-by-step guidance, practical examples, and best practices for putting Cluster API to work in your environments.
Understanding the basics of Cluster API
Let’s recap some basics. CAPI is a project maintained by the CNCF special interest group (SIG) Cluster Lifecycle Management.
Just as Kubernetes uses declarative APIs to manage containers, Cluster API introduces declarative Kubernetes-style APIs enabling you to create and manage clusters themselves.
It enables consistent and repeatable cluster deployments across a wide variety of infrastructure environments.
Setting up the environment
Before using Cluster API, you need to set up your environment. You must ensure that you have the necessary environments, such as GCP or AWS accounts and Kubernetes clusters, and the credentials required to access these resources.
Follow the steps below to set up your environment for Cluster API.
Install Kubernetes on your machine
If you do not already have Kubernetes installed on your machine, you can install it by following the guide on the official documentation for Kubernetes.
A Kubernetes cluster is a prerequisite for using Cluster API. This Kubernetes cluster is called the management cluster, and it does not need to be production-ready. Some of the popular ways to create and deploy a management cluster are by creating Kind or Minikube clusters.
Install Clusterctl and Kubectl
Clusterctl installs necessary CLI tools, Kubernetes manifests, and the required CRDs on the management cluster.
Kubectl is a command-line tool used for interacting with Kubernetes clusters. It is the primary interface for managing and controlling Kubernetes resources and workloads.
For MacOS, you can use Homebrew to install Kubectl and Clusterctl; for instance, run the command `brew install clusterctl` to install Clusterctl or `brew install kubectl` to install Kubectl.
Alternatively, you can download Clusterctl and Kubectl directly as a binary for other platforms.
Choosing your providers
Cluster API supports three types of providers: infrastructure, bootstrap, and control plane providers.
Infrastructure providers provision and manage the underlying infrastructure required for running Kubernetes clusters.
They handle tasks such as creating infrastructure like virtual machines, managing networking resources, and configuring storage.
The Cluster API project supports multiple infrastructure providers, allowing users to choose their preferred cloud or virtualization platform. Some examples of infrastructure providers include AWS, Azure, OpenStack and vSphere.
Bootstrap providers are responsible for bootstrapping the control plane nodes of the Kubernetes cluster.
They handle tasks such as installing the required software components and configuring the initial cluster state.
Cluster API supports multiple bootstrap providers to cater to different use cases. Some examples of bootstrap providers include Kubeadm, Kubeadm-bootstrap, etc.
Control plane providers
Control plane providers manage the Kubernetes control plane components, such as the API server, scheduler, and controller manager. They handle tasks such as scaling the control plane, upgrading components, and handling control plane failures.
Cluster API supports different control plane providers. Some examples of control plane providers include KubeadmControlPlane and ClusterAPI Provider for Docker (CAPD).
By combining different infrastructure, bootstrap, and control plane providers, Cluster API offers flexibility and choice to users in managing their Kubernetes clusters across various cloud and virtualization platforms.
The infrastructure provider is a compulsory component of the Cluster API setup, whereas bootstrap and control plane providers are optional. The bootstrap and control plane providers default to Kubeadm when not explicitly specified at setup.
Kubeadm (Kubernetes Administration) is the most popular tool that helps you bootstrap, deploy, and manage a Kubernetes cluster. It focuses on the initial deployment and basic cluster management tasks; hence, more advanced configurations and operations may require other Kubernetes tools and resources.
Setting up your infrastructure
For this post, we will set up a Cluster API with GCP and AWS providers. We therefore need to generate or collect necessary credentials such as:
- GCP Project ID
- GCE JSON key
- AWS Access Key ID
- Secret Access Key
You’ll need these to interact with Google and Amazon through the Kubernetes operator and Cluster API controller manager.
Configuring the Cluster API Provider for Google Cloud (CAPG) or Cluster API Provider for AWS (CAPA) typically involves providing specific environment variables or configuration settings.
While there isn't a standard "env file" that covers all CAPG or CAPA configurations, you can set environment variables in various ways, such as through a shell script or Kubernetes manifest.
Here's a general example of how you might configure CAPG or CAPA using environment variables in a shell script:
Create a shell script containing the CAPG or CAPA configuration
For GCP, create a shell file capg-config.sh, list your CAPG configuration variables. An example is shown below:
If your preferred cloud provider is AWS, create a shell file capa-config.sh and add the environment variables for your AWS environment using the example below as a guide:
Run the script
Make the script executable and run the script as shown below.
Note: The example above is for illustrative purposes. Actual CAPG or CAPA configurations and environment variable names may vary based on the version of CAPG or CAPA and the specifics of your setup.
Always check the official documentation and resources for accurate and up-to-date information on how to configure CAPG or CAPA for your cloud environment.
Setting up provider components
This typically involves installing CRDs, controllers, and a set of custom resources that drive the provider.
Run the following commands to install the provider components for AWS and GCP, respectively.
Creating and deploying the cluster
Once you have set up your environment and installed the providers, you can move on to cluster creation.
To create a workload cluster, you need to define a cluster object by specifying the desired state of the cluster.
This includes specifications for the number of nodes, Virtual Machines, networks, load balancers and other required resources.
Once created, the controller will ensure that the actual state matches the desired state.
You can now deploy your first Kubernetes cluster using Cluster API and the desired infrastructure provider.
The command below deploys a Kubernetes cluster named `my-cluster` in the `us-west1` region and creates its corresponding manifest.
Verifying that the cluster was created
Once the deployment is successful, you will need to verify whether the cluster exists or not.
Here you have to choose your approach.
You can check that the cluster has been created by monitoring the status of the cluster and machines custom resources from the management cluster. An example of how to do this is shown below:
You can also check the nodes with `kubectl get nodes`, but for that, you first need to download the kubeconfig file for the target cluster using `clusterctl get kubeconfig <name_of_the_target_cluster>` and switch context to it:
Note: If you're running a larger multi-environment or multi-cloud setup, you will create one manifest per cluster, or setup. You will end up with a lot of yaml files and a lot of scripts, and maintaining these efficiently is something you need to take seriously.
Managing the cluster
After creating a cluster object, you can manage your cluster like any other Kubernetes resource. This includes scaling up or down your cluster, updating configurations, and creating new resources like Nodes and Storage.
You can also use Kubernetes tools like Kubectl and Helm to manage the resources. Cluster API includes many tools, such as Clusterctl, that make it easier to manage your cluster.
If you're just starting with the concept of containerization, managing your cluster can prove difficult. Cluster API provides a unified way of defining, deploying, and managing Kubernetes clusters, making it easier to deploy and scale your containerized applications.
Troubleshooting and best practices
Like any other Kubernetes resource, troubleshooting Cluster API can be challenging.
If you're investigating Cluster API because you need to create and manage multiple clusters, there is an easier way.
Instead of having to create bootstrap clusters and understand operators, you can use a tool like Palette that is based on Cluster API and can build your clusters (and all the integrations) for you. Spectro Cloud, the organization behind Palette, actively contributes to CAPI providers, such as the Canonical MAAS provider for creating bare metal clusters.
As the CAPI docs say, “Cluster API is a Kubernetes sub-project focused on providing declarative APIs and tooling to simplify provisioning, upgrading, and operating multiple Kubernetes clusters.”
By simplifying the management of Kubernetes resources, organizations like yours can focus more on development and less on cluster management.
In this post, we went through the basics of Cluster API, including setting up the environment, creating a cluster, managing the cluster, and troubleshooting. We also mentioned some management platforms, such as Palette, that help you use CAPI more efficiently at scale.
The foundation of Palette is Cluster API, andWe hope that this guide has been helpful to you. Happy clustering!